IT2023 DIGITAL IMAGE PROCESSING L T P C
3 0 0 3
AIM:
The aim is to inculcate a basic training in the processing of images for practical applications in the domain of medical, remoting sessions and in general.
OBJECTIVES:
• To introduce basic concepts in acquiring, storage and Process of images
• To introduce for enhancing the quality of images.
• To introduce techniques for extraction and processing of region of interest
• To introduce case studies of Image Processing.
UNIT I FUNDAMENTALS OF IMAGE PROCESSING 9
Introduction – Steps in Image Processing Systems – Image Acquisition – Sampling and Quantization – Pixel Relationships – Colour Fundamentals and Models, File Formats, Image operations – Arithmetic, Geometric and Morphological.
UNIT II IMAGE ENHANCEMENT 9
Spatial Domain Gray level Transformations Histogram Processing Spatial Filtering – Smoothing and Sharpening. Frequency Domain : Filtering in Frequency Domain – DFT, FFT, DCT – Smoothing and Sharpening filters – Homomorphic Filtering.
UNIT III IMAGE SEGMENTATION AND FEATURE ANALYSIS 9
Detection of Discontinuities – Edge Operators – Edge Linking and Boundary Detection – Thresholding – Region Based Segmentation – Morphological WaterSheds – Motion Segmentation, Feature Analysis and Extraction.
UNIT IV MULTI RESOLUTION ANALYSIS AND COMPRESSIONS 9
Multi Resolution Analysis : Image Pyramids – Multi resolution expansion – Wavelet Transforms.
Image Compression : Fundamentals – Models – Elements of Information Theory – Error Free Compression – Lossy Compression – Compression Standards.
UNIT V APPLICATIONS OF IMAGE PROCESSING 9
Image Classification – Image Recognition – Image Understanding – Video Motion Analysis – Image Fusion – Steganography – Digital Compositing – Mosaics – Colour Image Processing..
TOTAL :45 PERIODS
TEXT BOOK:
1. Rafael C.Gonzalez and Richard E.Woods, “Digital Image Processing” Second Edition, Pearson Education, 200UNIT III
REFERENCES:
1. Milan Sonka, Vaclav Hlavac and Roger Boyle, “Image Processing, Analysis and Machine Vision”, Second Edition, Thomson Learning, 2001
2. Anil K.Jain, “Fundamentals of Digital Image Processing”, PHI, 2006.
3. Sanjit K. Mitra, & Giovanni L. Sicuranza, “Non Linear Image Processing”,
4. Elsevier, 2007.
5. Richard O. Duda, Peter E. HOF, David
3 0 0 3
AIM:
The aim is to inculcate a basic training in the processing of images for practical applications in the domain of medical, remoting sessions and in general.
OBJECTIVES:
• To introduce basic concepts in acquiring, storage and Process of images
• To introduce for enhancing the quality of images.
• To introduce techniques for extraction and processing of region of interest
• To introduce case studies of Image Processing.
UNIT I FUNDAMENTALS OF IMAGE PROCESSING 9
Introduction – Steps in Image Processing Systems – Image Acquisition – Sampling and Quantization – Pixel Relationships – Colour Fundamentals and Models, File Formats, Image operations – Arithmetic, Geometric and Morphological.
UNIT II IMAGE ENHANCEMENT 9
Spatial Domain Gray level Transformations Histogram Processing Spatial Filtering – Smoothing and Sharpening. Frequency Domain : Filtering in Frequency Domain – DFT, FFT, DCT – Smoothing and Sharpening filters – Homomorphic Filtering.
UNIT III IMAGE SEGMENTATION AND FEATURE ANALYSIS 9
Detection of Discontinuities – Edge Operators – Edge Linking and Boundary Detection – Thresholding – Region Based Segmentation – Morphological WaterSheds – Motion Segmentation, Feature Analysis and Extraction.
UNIT IV MULTI RESOLUTION ANALYSIS AND COMPRESSIONS 9
Multi Resolution Analysis : Image Pyramids – Multi resolution expansion – Wavelet Transforms.
Image Compression : Fundamentals – Models – Elements of Information Theory – Error Free Compression – Lossy Compression – Compression Standards.
UNIT V APPLICATIONS OF IMAGE PROCESSING 9
Image Classification – Image Recognition – Image Understanding – Video Motion Analysis – Image Fusion – Steganography – Digital Compositing – Mosaics – Colour Image Processing..
TOTAL :45 PERIODS
TEXT BOOK:
1. Rafael C.Gonzalez and Richard E.Woods, “Digital Image Processing” Second Edition, Pearson Education, 200UNIT III
REFERENCES:
1. Milan Sonka, Vaclav Hlavac and Roger Boyle, “Image Processing, Analysis and Machine Vision”, Second Edition, Thomson Learning, 2001
2. Anil K.Jain, “Fundamentals of Digital Image Processing”, PHI, 2006.
3. Sanjit K. Mitra, & Giovanni L. Sicuranza, “Non Linear Image Processing”,
4. Elsevier, 2007.
5. Richard O. Duda, Peter E. HOF, David
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